Trades Enriched

The common.predictions.kalshi_trades_enriched table provides enhanced trade data with market metadata, series tags, and estimated fees for the schedule in force on trade_date. Use this table for advanced analytics, market research, category analysis, outcome tracking, and fee analysis across Kalshi prediction markets.

Kalshi’s published trade-fee schedule is:

taker: M_taker × 0.07 × C × P × (1 − P)
maker: M_maker × 0.0175 × C × P × (1 − P)

C is num_contracts, P is yes_price, and (1 − P) is no_price. M_taker is taker_fee_multiplier (default 1). M_maker is maker_fee_multiplier (1 when the series charges maker fees, otherwise 0).Each side is rounded up to the next $0.0001. fee_usd is taker_fee_usd + maker_fee_usd. Kalshi may then add a rounding fee so the account balance lands on a clean increment, and may rebate a penny across fills of the same order. Those two steps are not in these columns. See Kalshi fee rounding.is_fee_schedule_inferred is true when the day’s multipliers use Kalshi’s standard schedule because no recorded fee change covers that date. The fee-change log begins 2025-10-04.

Table Columns

Data Precision Notes:

Prices are stored as floats on a 0-1 scale (e.g., 0.65 = $0.65)
Each contract is worth $1 at settlement
Includes all columns from the trades table plus market metadata, series tags, and fees

Unique Key: trade_id

Column Name	Data Type	Description
project	VARCHAR	Project identifier, always ‘kalshi’.
protocol	VARCHAR	Protocol identifier, always ‘kalshi’.
trade_date	DATE	Date of the trade (used for partitioning).
created_time	TIMESTAMP_NTZ(9)	Timestamp when the trade was created.
trade_id	VARCHAR	Unique identifier for the trade.
ticker	VARCHAR	Market ticker identifier for this trade.
num_contracts	NUMBER	Number of contracts traded in this trade.
taker_side	VARCHAR	Side taken by the taker (yes or no).
maker_side	VARCHAR	Side taken by the maker (opposite of taker_side).
yes_price	FLOAT	Price for “yes” outcome as a float (0-1 scale).
no_price	FLOAT	Price for “no” outcome as a float (0-1 scale).
taker_price	FLOAT	Price paid by the taker based on taker_side.
market_event_id	VARCHAR	Event identifier for the market.
market_series_id	VARCHAR	Series ticker for the market.
is_mve	BOOLEAN	True when the market is a multi-variable event.
market_name	VARCHAR	Market name.
market_question	VARCHAR	Market question text.
market_description	VARCHAR	Market description.
market_category	VARCHAR	Market category classification.
market_status	VARCHAR	Current status of the market.
market_start_date	TIMESTAMP_NTZ(9)	Timestamp when the market opened for trading.
market_end_date	TIMESTAMP_NTZ(9)	Timestamp when the market closes for trading.
market_expected_expiration_time	TIMESTAMP_NTZ(9)	Expected timestamp for market expiration.
market_expiration_time	TIMESTAMP_NTZ(9)	Actual expiration timestamp of the market.
market_outcome	VARCHAR	Market outcome resolution.
market_resolved_at	TIMESTAMP_NTZ(9)	Timestamp when the market was resolved.
series_title	VARCHAR	Series title from the series API.
series_category	VARCHAR	Series category from the series API.
series_tags	VARIANT	Series topic tags from the series API.
fee_type	VARCHAR	Fee formula in force on trade_date.
taker_fee_multiplier	FLOAT	Taker multiplier in force on trade_date.
maker_fee_multiplier	FLOAT	Maker multiplier in force on trade_date. 1 when the series charges maker fees, otherwise 0.
is_fee_schedule_inferred	BOOLEAN	True when the day’s multipliers use Kalshi’s standard schedule because no recorded fee change covers that date.
taker_fee_usd	FLOAT	Taker trade fee in USD, rounded up to the next $0.0001. Does not include Kalshi’s later rounding fee or per-order rebate.
maker_fee_usd	FLOAT	Maker trade fee in USD, rounded up to the next $0.0001. Zero when the series has no maker fee. Does not include Kalshi’s later rounding fee or per-order rebate.
fee_usd	FLOAT	Venue trade fee in USD: taker_fee_usd + maker_fee_usd. Does not include Kalshi’s later rounding fee or per-order rebate.
_created_at	TIMESTAMP_NTZ(9)	Timestamp of the entry creation on Allium’s database.
_updated_at	TIMESTAMP_NTZ(9)	Timestamp of the entry update on Allium’s database.

Sample Query

select
  trade_id,
  ticker,
  series_title,
  num_contracts,
  yes_price,
  no_price,
  fee_type,
  taker_fee_multiplier,
  maker_fee_multiplier,
  taker_fee_usd,
  maker_fee_usd,
  fee_usd
from common.predictions.kalshi_trades_enriched
where trade_date = '2026-08-24'
order by fee_usd desc
limit 100

Overview

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Table Columns

Sample Query

​Table Columns

​Sample Query

Table Columns

Sample Query